UPDATE: listChatbot

app.py

@@ -416,10 +416,10 @@ async def answerQuestion(request: Request, query: str, vectorstore: str, llmMode
 
 
 @app.post("/deleteChatbot")
-async def deleteChatbot(chatbotName: str):
-    username, chatbotName = chatbotName.split("$")[1], chatbotName.split("$")[2]
+async def deleteChatbot(vectorstore: str):
+    username, chatbotName = vectorstore.split("$")[1], vectorstore.split("$")[2]
     supabase.table('ConversAI_ChatbotInfo').delete().eq('user_id', username).eq('chatbotname', chatbotName).execute()
-    return deleteTable(tableName=chatbotName)
+    return deleteTable(tableName=vectorstore)
 
 
 @app.post("/listChatbots")
@@ -513,6 +513,45 @@ async def listChatbotSources(vectorstore: str):
     return result
 
 
+@app.post("/deleteChatbotSource")
+async def deleteChatbotSource(dataSourceName: str):
+    response = supabase.table("ConversAI_ChatbotDataSources").delete().eq("dataSourceName", dataSourceName).execute()
+    response = supabase.storage.from_('ConversAI_ChatbotDataSources').remove(dataSourceName)
+    return {
+        "output": "SUCCESS"
+    }
+
+
+class LoadEditedJson(BaseModel):
+    vectorstore: str
+    dataSourceName: str
+    sourceEndpoint: str
+    jsonData: dict[str, str]
+
+
+@app.post("/loadEditedJson")
+async def loadEditedJson(loadEditedJsonConfig: LoadEditedJson):
+    username, chatbotName = loadEditedJsonConfig.vectorstore.split("$")[1], loadEditedJsonConfig.vectorstore.split("$")[2]
+    jsonData = json.dumps(loadEditedJsonConfig.jsonData, indent = 1).encode("utf-8")
+    fileName = createDataSourceName(loadEditedJsonConfig.dataSourceName)
+    response = supabase.storage.from_("ConversAI").upload(file=jsonData, path=f"{fileName}_data.json")
+    response = (
+        supabase.table("ConversAI_ChatbotDataSources")
+        .insert({"username": username,
+                 "chatbotName": chatbotName,
+                 "dataSourceName": fileName,
+                 "sourceEndpoint": loadEditedJsonConfig.sourceEndpoint,
+                 "sourceContentURL": os.path.join(os.environ["SUPABASE_PUBLIC_BASE_URL"], f"{fileName}_data.json")})
+        .execute()
+    )
+
+    return {
+        "output": "SUCCESS"
+    }
+
+
+
+
 class TrainChatbot(BaseModel):
     vectorstore: str
     urls: list[str]